The Next Business Models of Web3
Early innovation in Web3 was and is centered on cryptocurrencies and Decentralized Finance (DeFi). Companies in these areas are building decentralized versions of traditionally centralized financial institutions (banks, exchanges, payments). Although many of these businesses remain in their early stages, they have already created billions of financial value (although less recently, with the market sell-off).
However, as Web3 continues to mature, I am beginning to see interesting companies (/DAOs/networks/projects) being built in what I think of as “applied DeFi”. These are companies that apply some of the capabilities of Web3 (tokenization, smart contracts, incentive structures), but in ways that either:
- Sit on top of existing centralized, even analog, systems, with the goal of transforming those systems
- Digitize and incentivize outcomes in the physical world
If successful, these companies will use Web3 capabilities to drive tangible outcomes in real-world environments, with (for many of these companies) a real sustainability impact.
Although it is early days for many of these projects, I see three broad “business models” arising in this space, with interesting innovation happening in each of the three.
Tokenization
Tokenization involves taking an asset that was previously off-line (or at least off-chain) and moving it on-chain. This theoretically provides several benefits, including:
- Transparency of asset history and ownership
- Liquidity
- Additional functionality of the asset (by unlocking its ability to be used in the broader Web3 financial ecosystem, e.g. staking)
Most prominently, in the climate space, you see this business model arising to manage carbon offsets. Innovators are transferring carbon offsets from traditional off-chain registries (e.g. Verra) to on-chain carbon ledgers. These offset-equivalents can then be traded or retired (and often, additional digital assets are unlocked by retiring the offsets).
Additionally, you see this business model applied in supply chain traceability applications — tracking raw materials from source to product, thus allowing businesses to prove provenance and ethical sourcing practices.
Tokenization companies are transforming “supply” that already exists in the market, imbuing this supply with additional information and utility in a bid to increase the attractiveness of the asset. If successful, this will unlock increased demand for these assets, which will be demonstrated by a price or demand premium for tokenized assets (versus non-tokenized assets).
Example Innovators: Toucan (carbon), Klima (carbon), Circulor (supply chain), Everledger (supply chain), Circularise (supply chain)
Collective Action
Included among any list of the defining social trends of the last 5 to 10 years should be 1) coordinated action, enabled by social media, and 2) the democratization of finance. These trends famously converged in the GameStop investing movement of 2020.
There is potential to harness similar energy with the tools of Web3. Web3 capabilities (tokenization, smart contracts) can be used to efficiently bring together “amateurs” who can wield their money, collectively, like professionals.
In climate, we see Web3 innovators building platforms to fund projects like reforestation and sustainable agriculture. These platforms coordinate demand for a specific project or projects from like-minded investors. They may also provide digital tools for the supply side of the market, allowing suppliers to easily create and credential their projects.
Although these platforms are early, they may someday allow retail investors to protect forests as easily as they trade stocks, and earn a return while doing so!
Example Innovators: Single.Earth, Regen Network, AllInfra, BasinDao
Networks
Finally, we have Web3 networks.
Traditional networks face a cold-start problem. Consider, for example, Uber — a classic example of a successful network. But, how do you start a business like Uber? If you just built the Uber app, and launched it, no one would use it. There would be no point in consumers going onto the app to check for rides, because there would be no drivers. But, if no one is requesting rides, no drivers are going to sign up either. Therefore, networks have a “chicken and an egg” problem — they aren’t valuable to consumers without supply, and suppliers won’t join without demand.
This often results in inefficiency in the early days of networks. Networks typically spend to build liquidity, for example by offering extreme discounts to bring in early demand. So, these networks can burn a lot of cash as they grow. But, what if there was another way?
With Web3 networks, there may be. A Web3 network mints its own token, which it uses to reward “suppliers” of the network.Then, it creates (theoretically) a natural demand for said token by requiring the use of the token in purchasing the services of the network. These are therefore referred to as “utility” tokens.
So, imagine a Web3 Uber — let’s call it Ub3r. To start Ub3r, I would create a $RIDE token, and stipulate that anyone providing rides would get paid in $RIDE. Furthermore, the amount of $RIDE the drivers earn per trip would decrease as the density of the network increases (analogous to how surge pricing works today — you get paid more when there are less other drivers available).
Now, why would this be successful at attracting drivers? Well, the early drivers would essentially become investors in the company. They could receive significant amounts of $RIDE early on, and as the company grows, and demand for $RIDE increases, that early $RIDE could greatly increase in value. So, suppliers may be willing to join the network early, potentially even when it is uneconomic to do so, if they believe in the vision of the company and think there is “upside” to their $RIDE.
Now, designing the correct incentive structure for these networks is referred to as “tokenomics”, and it is not a simple problem. You need to ensure the rewards are generous enough to incentivize early participants, but not so generous that you don’t have enough token supply to continuously offer attractive economics to suppliers even as the network scales. Additionally, you need some tokens for investors and employees! Figuring out the right balance of token rewards is something that I anticipate will become more refined as these networks scale — you could easily imagine that in 5 years there are a few “rules of thumb” that may not quite exist today.
However, the token-based strategy has one major advantage, in that it is not as reliant on external stakeholders (i.e. investors). Therefore, it can scale more quickly. Additionally, proponents would argue that it better aligns incentives between the builders of the network and its users — everyone shares in the rewards as the network becomes more popular and useful. This could make the networks more sustainable in the long term, as they will not be required to repeatedly raise prices on their users to increase profitability.
These networks are mostly still in their early days, but when they hit on a compelling use case, they can scale extremely rapidly. Helium (5G hotspots) is the best example of this. Helium grew from 14K hotspots on its network to 400K in just one year (Dec. 2020 to Dec 2021), due to excitement around the Helium vision and the compelling economics of being an early supplier. Now, they have a large telecom platform, and are building partnerships with traditional telecom players like DISH to provide connectivity services.
Example Innovators: Helium (mobile hotspots), PlanetWatch (environmental sensing), Hivemapper (mapping), DIMO (connected vehicles), Constellation (occupancy tracking)
Conclusion
So, those are the business models of some interesting innovators I am seeing in Web3. This entire ecosystem is early, but the nature of Web3 incentive models allows these companies, if they hit on a great use case, to scale very quickly. So, this market bears watching closely, and I expect to see more success stories over the next few years! If you are working on something interesting in this space, feel free to reach out — I would love to learn more!
